Raullen R Email & Phone Number
@iotex.io
2 phones found area 650
LinkedIn matched
Who is Raullen R? Overview
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Raullen R is listed as Co-Founder and CEO at MachineFi Lab, a company with 4 employees, based in United States, United States, United States. AeroLeads shows a work email signal at iotex.io, phone signal with area code 650, and a matched LinkedIn profile for Raullen R.
Raullen R previously worked as Co-Founder & CEO at Machinefi Lab and Co-Founder & CEO at Iotex: A Decentralized Network For Internet Of Things. Raullen R holds Ph.D, Electrical & Computer Engineering from University Of Waterloo.
Email format at MachineFi Lab
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AeroLeads found 1 current-domain work email signal for Raullen R. Compare company email patterns before reaching out.
About Raullen R
Founded as an open-source project in 2017, IoTeX envisions bringing together people, process, data and things with trust and free will to create new capabilities, richer experiences, and unprecedented economic opportunity. Our platform, serving as the global trust backbone for intelligently and efficiently connecting distinct parties, is built from scratch by former tech leads from Google, Facebook, Uber, Intel, Bosch, and is based our innovations in blockchain, identity, confidential computing, and edge cloud.I would like to meet technologists, entrepreneurs, and investors who are interested in creating the decentralized world of connected machines.
Listed skills include Algorithms, Python, C++, Java, and 21 others.
Raullen R's current company
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Raullen R work experience
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Co-Founder & Ceo
Current
Co-Founder & Ceo
CurrentWe are actively hiring. Drop me a line if you want to join us to work on the next generation of blockchain technology!
Member Indutrial Distributed Ledger Task Group
Lead Of Crypto R&D And Engineering Security
Lead the crypto team to design and develop cryptography platforms, services and tools to address business needs, e.g., KMS, PKI, IAM, Auth and crypto SDK.
Senior Software Engineer / Tech Lead
Founding engineer of Google Cloud Load Balancer (https://cloud.google.com/load-balancing/), designed and led areas like high-throughput distributed data-pushing, SSL offload, HTTPs load balancing, stackdriver logging, backend authentication and auto-scaling; Leading contributor of Google's reverse proxying system that terminates user traffic, performs.
Member Of Technical Staff
Lead the design and implementation of security features for Oracle Enterprise Search (http://www.oracle.com/technetwork/search/oses/overview/index.html) including Auth{N, Z}, Identity Management, Encryption and Privacy Enhancement.
Research Fellow
Continue research on:-- Lightweight Cryptography-- Security and Privacy in Internet of Things (IoT)-- Privacy-Preserving Techniques for Blockchain
Raullen R education
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University Of Waterloo
Frequently asked questions about Raullen R
Quick answers generated from the profile data available on this page.
What company does Raullen R work for?
Raullen R works for MachineFi Lab.
What is Raullen R's role at MachineFi Lab?
Raullen R is listed as Co-Founder and CEO at MachineFi Lab.
What is Raullen R's email address?
AeroLeads has found 1 work email signal at @iotex.io for Raullen R at MachineFi Lab.
What is Raullen R's phone number?
AeroLeads has found 2 phone signal(s) with area code 650 for Raullen R at MachineFi Lab.
Where is Raullen R based?
Raullen R is based in United States, United States, United States while working with MachineFi Lab.
What companies has Raullen R worked for?
Raullen R has worked for Machinefi Lab, Iotex: A Decentralized Network For Internet Of Things, Industrial Internet Consortium, Uber, and Google.
How can I contact Raullen R?
You can use AeroLeads to view verified contact signals for Raullen R at MachineFi Lab, including work email, phone, and LinkedIn data when available.
What schools did Raullen R attend?
Raullen R holds Ph.D, Electrical & Computer Engineering from University Of Waterloo.
What skills is Raullen R known for?
Raullen R is listed with skills including Algorithms, Python, C++, Java, Eclipse, C, Embedded Systems, and Machine Learning.
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